DeBERTa: `from_pretrained(dtype=torch.bfloat16)` leaves `q_bias`/`v_bias` in float32, forward fails (`expected m1 and m2 to have the same dtype`)
Public issue #50200 in huggingface/transformers. The source issue contains the full report and discussion.
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Reported problem
The record contains the title “DeBERTa: `from_pretrained(dtype=torch.bfloat16)` leaves `q_bias`/`v_bias` in float32, forward fails (`expected m1 and m2 to have the same dtype`)” but no substantive source summary.
Frequency & alternatives
This is one problem record. Independent user counts, task frequency and existing spending have not been established.
Demand hypothesis
Treat the reported task or obstacle as an interview lead. A feature request, complaint or search for alternatives does not by itself identify a budget owner or willingness to pay.
Commercial evidence gaps
Missing evidence: distinct affected users, repeated occasions, current workaround, measured time or money cost, purchasing authority and a response to a concrete offer.
Validation decision
Group original reports by the same task and deduplicate authors and reposts. Ask how the task is handled today and what it costs; test a defined offer before claiming paid demand.